A new characterization model of FinFET self-heating effect based on FinFET characteristic parameter

The characterization of the self-heating effect (SHE) has been an important research topic in advanced technology, but the existing characterizations are few and the characterization process is relatively complex. In this research, a SHE characterization model is established based on the relationship between output transconductance variation (Delta(gm)), gate source voltage (V-GS) and temperature variation (triangle T) caused by SHE through machine learning, and then the model is validated by theoretical analyses and experimental simulation. The characterization model is capable of directly calculating the triangle T caused by SHE during I - V testing and simplifying the SHE characterization steps while ensuring characterization accuracy (triangle T difference < 1 degrees C), thus saving costs. It is also found that the model can expand the characterization range (V-GS: 0.3-0.7 V) of SHE and conducts quantitative characterization with model calculation under different V-GS, realizing a high characterization resolution of V-GS: 0.01 V. The circuit level application proves that the method can be effectively applied to the characterization of the SHE and solves the problem of the characterization of the circuit level SHE.